EP3410329B1 - Procédé et système de détection des entrées irrégulières pour des applications de traitement de données - Google Patents

Procédé et système de détection des entrées irrégulières pour des applications de traitement de données Download PDF

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Publication number
EP3410329B1
EP3410329B1 EP17173704.2A EP17173704A EP3410329B1 EP 3410329 B1 EP3410329 B1 EP 3410329B1 EP 17173704 A EP17173704 A EP 17173704A EP 3410329 B1 EP3410329 B1 EP 3410329B1
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Prior art keywords
vector
duration
determined
input
capturing
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EP17173704.2A
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German (de)
English (en)
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EP3410329A1 (fr
Inventor
Oliver Schmuhl
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Deutsche Telekom AG
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Deutsche Telekom AG
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
    • G06F21/31—User authentication
    • G06F21/316—User authentication by observing the pattern of computer usage, e.g. typical user behaviour
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2221/00—Indexing scheme relating to security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F2221/21—Indexing scheme relating to G06F21/00 and subgroups addressing additional information or applications relating to security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F2221/2133—Verifying human interaction, e.g., Captcha

Definitions

  • the invention relates to the field of data processing, in particular to a method and system for detecting irregular inputs for data processing applications.
  • Application examples for a system and method according to the invention include applications with user interaction, for example content and services accessible on the Internet, in which a software-based delimitation and differentiation from automated linear inputs is required.
  • the system and method according to the invention can be used as a Completely Automated Public Turing test to tell Computers and Humans Apart (CAPTCHA).
  • WO 2010/105249 A1 relates to a system and method for distinguishing human input events from malware generated events, wherein a first set of input events is generated by a user using the input device. The first input events are used to obtain or derive a characteristic that identifies the user.
  • CAPTCHA systems are used to increase security against unwanted automated access.
  • Human senses are often used, for example the solution to a visually presented problem that cannot usually be captured by a computer is used. Alternatively, sound or video sequences are used.
  • An evaluation created in this way can be used as a CAPTCHA because it allows a differentiation and differentiation from automated linear, ie regular, entries.
  • the time of the start, hold and end of the various input signals from input devices is continuously measured, preferably in milliseconds or smaller time units. Based on the measured values determined, the duration of the individual input signals and the pauses between the input signals are calculated.
  • a set for the individual values with the duration of individual signals and a set for the individual values with the duration of the pause between individual signals are searched for in these quantities and a numerical indicator value, for example based on the number of irregularities, and/or a pattern/fingerprint of the quantities is created from this.
  • the indicator value can be used to delimit and differentiate manual inputs from automated linear individual inputs, i.e. the input behavior of the individual signals.
  • the fingerprint is used to delineate and differentiate from automated linear total inputs, i.e. a total input behavior of all signals, and/or a collection and comparison of at least two captured input sequences.
  • the point in time, preferably in milliseconds or less, of the arrival, stopping and ending of the various input signals from input devices, preferably a keyboard, is measured.
  • the time is measured from the occurrence of the signals: key-down, i.e. pressing a key, and key-up, i.e. releasing a key.
  • Other embodiments may relate to other input devices.
  • Other input devices are preferably a touch screen, a mouse, or voice input. In particular, however, the signal from special input devices for the physically handicapped can also be detected.
  • the duration between the signals: key-down and key-up is determined from the data measurement. This value provides the duration of an input, in the above embodiment the duration of a keystroke.
  • the second value is the duration between key-up and key-down. This value returns the pause between two inputs, i.e. two keystrokes.
  • the data determined is stored continuously in the memory of the DP system in full and/or to a limited extent in value tables, which represent the simplest embodiment of the vectors according to the invention.
  • value tables which represent the simplest embodiment of the vectors according to the invention.
  • tbS a table of values
  • tbP a table of values
  • All variants of the possible duration in the time scale used are used as keys for both value tables.
  • Table 1 Value table for the measurement in the range 0 - 255 ms (scaling milliseconds) key: ms 0 ... 100 101 102 103 104 105 106 107 ... 255 Value: Yes / No
  • the determined duration is used as the value. In this case, however, not as a value, but as a statement as to which of the possible variants fulfills a determined duration.
  • Table 2 Value table for a measurement of the value sequence: 101ms, 105ms, 107ms, 100ms, 107ms, 105ms , ... key: ms 0 ... 100 101 102 103 104 105 106 107 ... 255 Value: Yes / No X X X x key: ms 0 ... 100 101 102 103 104 105 106 107 ... 255 Value: Yes / No X X x key: ms 0 ... 100 101 102 103 104 105 106 107 ... 255 Value: Yes / No X
  • a number of irregularities is determined via the direct number of fulfilled variants in the value tables tbS and tbP.
  • the evaluation can be solved individually using mathematical and/or statistical methods. General statements are made about the ratio of the number of input signals to the number of detected irregularities or about the ratio of the number of detected to the maximum possible irregularities.
  • bit fields bmS and bmP are generated from the value tables tbS and tbP described. These two bit fields are also referred to as patterns.
  • Table 4 A table of values and the resulting bit field: 0...11000101...0 key: ms 0 ... 100 101 102 103 104 105 106 107 ... 255 Value: Yes / No X X X X
  • bit fields bmS and bmP are combined to form a common bit field bmX.
  • the data is used in binary form in its entirety or in an abbreviated form due to fuzziness and thus forms the fingerprint of the entire input behavior.
  • the bit field bmX is also referred to as a fingerprint.
  • the fingerprints created are stored in the data processing system and are used for a binary and/or fuzzy comparison. If a fingerprint occurs several times, this is an indication of an automated linear input, even if there is a sufficient number of irregularities in the input signal sequence.
  • figure 1 shows a block diagram of an embodiment of the method according to the invention and figure 2 an illustration of a temporal input sequence generated by a keyboard of a computer.
  • the input sequence figure 2 is obtained by pressing the A, B, and C keys on the keyboard.
  • the intervals for the durations tSn, tS n+1 and tS n+2 as well as tP n and tP n+1 are shown below the time axis, which are each of different lengths, in other words are irregular.
  • an input sequence 100 is first received.
  • a first optional filter device 101 checks whether the input sequence is relevant for the method. This filter unit increases the quality of the recording.
  • the durations tS n and tP n are determined in a time measuring device 201 .
  • the durations are associated with a vector 301 for the pause durations tP n and a vector 302 for the signal durations tS n .
  • An evaluation device 401 determines the irregularities and determines the indicator value and/or the fingerprint.
  • An external application 402, preferably a web service and/or web application, can access the indicator value and/or fingerprint provided by the evaluation device 401. This makes it possible to use it as a CAPTCHA, because human input will always have certain input characteristics, which can be determined and evaluated based on certain irregularities.
  • Figures 3a to 3c show a representation of a test result with manual input for an embodiment of the invention.
  • the entry "10318_Berlin” is made using a keyboard connected to a computer.
  • a program code that implements the method and system according to the invention works on the computer.
  • the detected inputs ie the measured time durations, the determined vectors tbS and tbP and the determined indicator value are shown. Since with the repeated inputs in Figures 3a to 3c If the manual input varies slightly, different vectors and an indicator value between 50 and 75% result.
  • FIG. 12 shows a representation of an experimental result with input by DOM manipulation for an embodiment of the invention.
  • the embodiment corresponds to the embodiment in FIGS Figures 3a to 3c .
  • DOM Document Object Model
  • FIG 5 shows a representation of a test result with input of a keyboard simulation in a first variant of an embodiment of the invention.
  • the embodiment corresponds to the embodiment in FIGS Figures 3a to 3c .
  • software solutions for automation that use the client API of browsers to simulate user interactions take up this manipulation method.
  • the keyboard simulation in the first variant sends an input, for example via an AutoHotKey function, ie an emulated input. Because of the emulation, only one element of each vector is occupied, resulting in constant indicator values of 10%. Such an attack can also be successfully detected compared to manual input.
  • Figures 6a to 6c a representation of a test result with input a keyboard simulation in a second variant for an embodiment of the invention.
  • the embodiment corresponds to the embodiment in FIGS Figures 3a to 3c .
  • the keyboard simulation in the first variant sends an input, for example via an AutoHotKey function, an emulated input.
  • Emulation inserts random pauses between input signals. Because of the emulation, only one element of the respective vectors tbS is occupied. However, there is a distribution in the occupancy of the vector tbP. Indicator values vary at 40%. Such an attack can also be successfully detected compared to manual input.
  • a further optimization of the emulation can enable an input that is almost identical to the manual input.
  • the evaluation is reduced to a very simple embodiment of the invention. This reduction does not limit the scope of protection.
  • a more complex analysis of the vector takes into account the population distribution of the vectors and/or their correlation.
  • the invention also includes individual features in the figures, even if they are shown there in connection with other features and/or are not mentioned above or below.
  • the alternative embodiments described in the figures and the description can also be excluded from the subject matter of the invention or from the disclosed objects.
  • the disclosure includes embodiments that exclusively include the features described in the claims or in the exemplary embodiments, as well as those that include additional other features.

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  • Engineering & Computer Science (AREA)
  • Computer Hardware Design (AREA)
  • General Engineering & Computer Science (AREA)
  • Computer Security & Cryptography (AREA)
  • Theoretical Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Social Psychology (AREA)
  • Software Systems (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Collating Specific Patterns (AREA)

Claims (5)

  1. Procédé de détection d'entrées irrégulières pour des applications de traitement de données, ledit procédé comprenant les étapes suivantes :
    a) détection d'une séquence de signaux d'entrée (100) dans une application de traitement de données provenant d'au moins une unité d'entrée physique et/ou virtuelle et détermination d'au moins deux temps de durée tS pour une durée de détection d'un signal d'entrée et d'au moins deux temps de durée tP pour une durée jusqu'à la détection d'un signal d'entrée suivant,
    b) formation d'un premier vecteur (302) avec, ou sur la base du temps de durée tS déterminé, et formation d'un deuxième vecteur (301) avec, ou sur la base du temps de durée tP déterminé,
    où une longueur du premier et du deuxième vecteurs est prédéterminée et les éléments du premier et du deuxième vecteurs correspondent à des intervalles temporels prédéterminés consécutifs jusqu'à une durée de détection tMax maximale ;
    où les valeurs des éléments du premier et du deuxième vecteurs présentent des propriétés booléennes ;
    où une empreinte digitale (401) de l'entrée est déterminée, par conversion du premier et du deuxième vecteurs en un champ de bits chacun, et couplage en un champ de bits commun des champs de bits du premier et du deuxième vecteurs dans leur totalité ou par flou sous forme raccourcie ; et
    ledit procédé comprenant en outre les étapes suivantes :
    c) détermination d'irrégularités dans la séquence de signaux d'entrée par analyse de l'empreinte digitale, et
    d) préparation d'une valeur d'indication sur la base des irrégularités déterminées.
  2. Procédé selon la revendication 1,
    où, lors de l'étape a), le temps de durée tS est déterminé à partir du temps de durée mesuré entre un signal de touche enfoncée et un signal de touche relevée consécutif, et le temps de durée tP est déterminé à partir du temps de durée mesuré entre un signal de touche relevée et un signal de touche enfoncée consécutif.
  3. Procédé selon la revendication 1 ou la revendication 2,
    où, lors de l'étape c) l'analyse est basée sur au moins une analyse de ce qui suit :
    i) la densité d'occupation dans le premier et/ou le deuxième vecteur,
    ii) la distribution de valeurs dans le premier et/ou le deuxième vecteur,
    iii) une corrélation entre le premier et le deuxième vecteurs,
    iv) une corrélation entre le premier et/ou le deuxième vecteur et un vecteur prédéterminé.
  4. Procédé selon l'une des revendications 1 à 3,
    où la valeur d'indication est basée sur le rapport entre la somme des éléments de vecteur occupés du premier et/ou du deuxième vecteur et un nombre d'entrées détectées.
  5. Système pour la détection d'entrées irrégulières pour des applications de traitement de données, ledit système comprenant :
    une unité de détection de signaux, configurée pour détecter une séquence de signaux d'entrée d'au moins une unité d'entrée physique et/ou virtuelle, et configurée pour déterminer au moins deux temps de durée tS pour une durée de détection d'un signal d'entrée et au moins deux temps de durée tP pour une durée jusqu'à la détection d'un signal d'entrée suivant ;
    une unité de traitement de signaux, configurée pour former un premier vecteur sur la base du temps de durée tS déterminé et un deuxième vecteur sur la base du temps de durée tP déterminé ;
    où une longueur du premier et du deuxième vecteurs est prédéterminée et les éléments du premier et du deuxième vecteurs correspondent à des intervalles temporels prédéterminés consécutifs jusqu'à une durée de détection tMax maximale ;
    où les valeurs des éléments du premier et du deuxième vecteurs présentent des propriétés booléennes ;
    où une empreinte digitale de l'entrée est déterminée, par conversion du premier et du deuxième vecteurs en un champ de bits chacun, et couplage en un champ de bits commun des champs de bits du premier et du deuxième vecteurs dans leur totalité ou par flou sous forme raccourcie ; et
    ledit système comprenant en outre :
    une unité d'analyse, configurée pour déterminer des irrégularités dans le signal d'entrée par analyse de l'empreinte digitale ; et
    une unité d'indication, configurée pour préparer une valeur d'indication sur la base des irrégularités déterminées.
EP17173704.2A 2017-05-31 2017-05-31 Procédé et système de détection des entrées irrégulières pour des applications de traitement de données Active EP3410329B1 (fr)

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EP17173704.2A EP3410329B1 (fr) 2017-05-31 2017-05-31 Procédé et système de détection des entrées irrégulières pour des applications de traitement de données

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EP2406717A4 (fr) * 2009-03-13 2012-12-26 Univ Rutgers Systèmes et procédés pour détecter un logiciel malveillant
US9531733B2 (en) * 2010-11-29 2016-12-27 Biocatch Ltd. Device, system, and method of detecting a remote access user
WO2014205148A1 (fr) * 2013-06-19 2014-12-24 Arizona Board Of Regents For The University Of Arizona Outil d'authentification permanente

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